A Congestion-Preventing Routing and Charging Scheduling Mechanism for Electric Vehicles in Dense Urban Areas

被引:4
作者
Huang, Chenn-Jung [1 ]
Hu, Kai-Wen [2 ]
Ho, Hsing-Yi [1 ]
Chuang, Hung-Wen [1 ]
机构
[1] Natl Dong Hwa Univ, Dept Comp Sci & Informat Engn, 1,Sect 2,Da Hsueh Rd, Hualien 974301, Taiwan
[2] Natl Dong Hwa Univ, Dept Elect Engn, 1,Sect 2,Da Hsueh Rd, Hualien 974301, Taiwan
来源
INFORMATION TECHNOLOGY AND CONTROL | 2021年 / 50卷 / 02期
关键词
Optimization; electric vehicle; route and charging planning; congestion control; machine learning; REDUCE TRAFFIC CONGESTION; STRATEGY; SYSTEM; LIGHT;
D O I
10.5755/j01.itc.50.2.27780
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Traffic congestion in metropolitan areas all over the world has become a critical issue that governments must deal with effectively. Traffic congestion during rush hours causes vehicle drivers to arrive late at their destinations, resulting in significant economic losses. Although researchers have proposed solutions to the traffic congestion problem, little research work has presented a joint route and charging planning strategy for electric vehicles (EVs) that alleviates traffic congestion problems simultaneously. Accordingly, a congestion-preventing route and charging planning mechanism for EVs is proposed in this work to tackle the complicated route and charging optimization problems of EVs. The route and charging planning proposed in this work analyzes the information provided by EVs, the charging points, and road traffic information simultaneously, and mediates the traffic jamming by means of a route and charging reservation mechanism. Possible occurrence of traffic congestion is detected in advance and traffic regulation is carried out by allocating an elastic range to the traveling period for late-booking EVs, to avoid moving during rush hours. EV owners are also encouraged to provide rideshare services for late-booking EV users during rush hours. The simulation results reveal that the proposed work can satisfy the preferred route and charging demands of EV users and alleviate traffic congestion effectively.
引用
收藏
页码:284 / 307
页数:24
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